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Advanced manufacturing technologies (AMT) require considerable investments that managers often avoid, which makes it difficult to link their production operations with the benefits reported in literature review. The present paper shows a structural equation model that integrates four latent variables to measure the relationship between the levels of advanced manufacturing technologies implementation (Stand-Alone Intermediate and Integrated Systems), as well as the benefits obtained in the productive systems. The variables are related to each other using six hypotheses in order to realise how the AMT implementation level affects the benefits obtained from a quantitative and statistical point of view. The model is evaluated through the partial least square technique with data from 383 responses to a survey. Findings show that Stand-Alone Systems contribute more to obtaining Production Benefits, followed by Integrated Systems and Intermediate Systems. Finally, a sensitivity analysis based on conditional probabilities was performed to evaluate scenarios at different implementation levels in AMT to know how they facilitate the acquisition of the benefits offered.

The present research proposes a structural equation model to integrate four latent variables: managerial commitment, preventive maintenance, total productive maintenance, and productivity benefits. In addition, these variables are related through six research hypotheses that are validated using collected data from 368 surveys administered in the Mexican manufacturing industry. Consequently, the model is evaluated using partial least squares. The results show that managerial commitment is critical to achieve productivity benefits, while preventive maintenance is indispensable to total preventive maintenance. These results may encourage company managers to focus on managerial commitment and implement preventive maintenance programs to guarantee the success of total productive maintenance.